Okay. So, here we will talk about this normal distribution. So, normal distribution is one of the more important theory and nearly all status statistical testing require the data to be distributed normally. So, actually, why is a normal distribution? So, let's say I search the internet for normal distribution okay normal distribution should be something like what we call the bell curve. So, this is the mean.

And this is the first standard deviation. Data mean, mean standard deviation mean minus standard deviation. Then this one is the mean minus two times standard deviation, the mean ma plus two times standard deviation, the mean plus three times standard deviation, mean minus three times the standard deviation. So, this is how the normal distribution will look like it's like a Delta in our pa distribution, we can create a histogram of the histogram. So, in other histogram the brace is the number of bars in the histogram beings is the class interval two slugger data. So for our program, our programming histogram function, we will be using the brace beans is not in the histogram function here.

So let's see if I were to draw a histogram. So I can do something like this. So, histogram data sepal length then the brace I can pull something like 15 So, breaks equal 50 So, I have a histogram here, so this is not so normally distributed. So let's say I try race equal 10 so the data is not really normally distributed okay. So I cannot include ah Mr bricks here okay so is not normally distributed. So, he co Grameen we can find a distribution using histogram We can also see whether data is normally distributed using qq norm function and qq line.

So, I can do something like this qq norm in our data. So, I will do qq norm data sepal and qq lie data sepal length Okay, for cuckoo proc, ah bodies our data objects is, let's say closer to this light here. Then we can say that distribution is normally distributed, gave the data objects or data policies are let's see way further away from this line here, then we can say this our data is not very normally distributed. So we can also use sharp shop Halo test to test whether the data is normally distributed. So you can use Schapiro to test something IDs. So Schapiro test data set.

So our P value is 0.01. So let's see if the p value is more than 0.05. We can conclude that our data is not debatable. Normal distribution. So, for our result here, our P value is 0.01. So, r is less than 0.05.

So, we can conclude that the data is deviated from normal distribution meaning that a tie is not really also normally distributed. So, this is how, let's say in our programming we can see whether data is normally distributed, we can use histogram, qq, line qq norm and Schapiro tests. So this is how we can see whether data is normally distributed in our programming.